Author: Jeremie Harris

What Can Artificial Intelligence Teach Us About Political Polarization?

It’s become increasingly difficult to ignore the exponential progress that’s been made in the field of artificial intelligence. From self-driving cars to nearly flawless speech synthesis, things most of us thought impossible only a decade ago are now a practical reality. Virtually all of these developments have exploited what has turned out to be one of the most fruitful analogies ever made: that of the human brain to a computer. In particular, the development of neural networks—arguably the most successful family of artificial intelligence models—was explicitly inspired by the structure and function of the brain. For about a decade, we’ve exploited the brain/computer analogy by drawing inspiration from the brain to build better and better AI systems. But now that our technology has in many respects caught up to, and even exceeded, human performance, it’s worth asking the question in reverse: what insights can we borrow from artificial intelligence, to better understand our own brains and reasoning processes, and how they can go wrong? As it turns out, there are quite a few, and they …